code: def output_F(outfile, contrast, fmri_image, clobber=False):
      """output F statistic images
  
      Parameters
      ----------
      outfile : str
          filename for F contrast image
      contrast : array
          F contrast matrix
      fmri_image : ``FmriImageList`` or ``Image``
          object such that ``object[0]`` has attributes ``shape`` and
          ``coordmap``
      clobber : bool
          if True, overwrites previous output; if False, raises error
  
      Returns
      -------
      f_reg_out : ``RegressionOutput`` instance
          Object that can a) be called with a results instance as argument,
          returning an array, and b) accept the output array for storing, via
          ``obj[slice_spec] = arr`` type slicing.
      """
      f = ModelOutputImage(
          outfile,
          fmri_image[0].coordmap,
          fmri_image[0].shape,
          clobber=clobber,
      )
      return outputters.RegressionOutput(
          f, lambda x: outputters.output_F(x, contrast)
      )
  
imports: import copy
  from os import path
  import numpy
  import numpy.linalg
  from nipy.algorithms.statistics.formula import make_recarray
  from nipy.algorithms.statistics.models.regression import ARModel, OLSModel, ar_bias_correct, ar_bias_corrector
  from nipy.core.api import AffineTransform, Image, matrix_generator, parcels
  from nipy.io.api import save_image
  from ..api import FmriImageList, axis0_generator
  from .None import outputters
label_desc: Use image node_id 5 for calling a global function with example usage: output_F(outfile, contrast, fmri_image, clobber) and returns: outputters